The Data Miner’s job is a specialization of the Data scientist‘s job, which focuses on the data exploration part: which data is useful? Do I need to add open data to get relevant results? Do I need to build specific algorithms to explore my data?
What are his Objectives?
The Data Miner make the company’s data talk. He/she is responsible for reading and analyzing the company’s data and must therefore understand the company’s business issues in order to provide the relevant data that will respond to these issues.
He/she knows and masters database storage and management structures, knows how to create SQL queries and work on structured or unstructured databases. This work has long been considered complex and thankless, because its first objective is to find the data that will be useful and to clean it. Only then can he analyze and provide the data he finds interesting to the appropriate department, historically Marketing. The Data Miner was in the shadow of marketing decisions but now it is in the light. The job has evolved somewhat beyond data extraction, cleaning and sorting to become Data Science. In short, the Data Miner only captures quality data that will be analyzed by the business units or processed by other teams in the data lab to “make them talk”.
What Skills are Needed?
The qualities required for the Data Miner’s job are a very solid IT background, particularly in the mastery of DBMS (Database Management System), a very good command of statistical mathematics and a business sense, in order to understand and translate business issues into : “what data will they need to solve this problem? ». The statistics-oriented mathematics courses have not been very successful in recent years, which makes it very difficult for employers to find data miner profiles. But the professions of Data Analyst, Data Scientist, Data Engineer, are now dusting off these training courses thanks to the attention that Data Science or Big Data are getting. The field of action of the Data Miner, even if historically this profession has emerged in the field of marketing, is much wider, and even today goes as far as Machine Learning. The Data Miner will be able to intervene in areas as diverse as the retention of customers of a brand or brand name, by analyzing the behavior of “cohorts” in order to push consumers towards offers that have a good chance of “competing”, or on market segmentation. They can also intervene in the industry with use cases on predictive maintenance or by developing sales forecasting algorithms to optimize the flow and inventory of companies.
The Missions of the Data Miner
- Collect data and data processing, create algorithms to analyze the quality of the database, variables of interest to exploit, add relevant data from the open data…
- Extract and analyze data (creation of algorithms to explore the data, detect weak signals…)
- Carrying out qualitative and quantitative analysis in order to respond to business issues